AbstractWe give a simple framework for computing relative convergence rates for relaxation methods with discrete Laplace operators (five point or nine point). This gives relations between the convergence rate for Jacobi, point Gauss Seidel, and various block relaxation strategies, essentially by inspection. The framework is a random walk interpretation of Jacobi relaxation that extends to these other relaxation methods
AbstractWe obtain rates of convergence of stochastic relaxation (heat bath algorithm) for continuous...
The problem (LFP) of finding a feasible solution to a given linear semi-infinite system arises in d...
Convergent sequences of real numbers play a fundamental role in many different problems in system th...
AbstractWe give a simple framework for computing relative convergence rates for relaxation methods w...
AbstractThe rate of convergence of various sweep strategies of stochastic relaxation for simulating ...
We study convergence properties of time-point relaxation (TR) Runge-Kutta methods for linear systems...
AbstractWhen convergent Jacobi or Gauss-Seidel iterations can be applied to solve systems of linear ...
AbstractWe study convergence properties of time-point relaxation (TR) Runge-Kutta methods for linear...
The Scheduled Relaxation Jacobi (SRJ) method is an extension of the classical Jacobi iterative metho...
International audienceIn the framework of linear problems, a usual approach to study the convergence...
Abstract: Non-linear renewal theory is extended to include random walks perturbed by both a slowly c...
Extrapolation methods to accelerate convergence of a sequence of iterates are in-vestigated. A trans...
International audienceWe study convergence rates of R-d-valued algorithms, especially in the case of...
The connection between the conditioning of a problem instance -- the sensitivity of a problem instan...
We propose a new approach to analyze the convergence of optimized Schwarz waveform relaxation (OSWR)...
AbstractWe obtain rates of convergence of stochastic relaxation (heat bath algorithm) for continuous...
The problem (LFP) of finding a feasible solution to a given linear semi-infinite system arises in d...
Convergent sequences of real numbers play a fundamental role in many different problems in system th...
AbstractWe give a simple framework for computing relative convergence rates for relaxation methods w...
AbstractThe rate of convergence of various sweep strategies of stochastic relaxation for simulating ...
We study convergence properties of time-point relaxation (TR) Runge-Kutta methods for linear systems...
AbstractWhen convergent Jacobi or Gauss-Seidel iterations can be applied to solve systems of linear ...
AbstractWe study convergence properties of time-point relaxation (TR) Runge-Kutta methods for linear...
The Scheduled Relaxation Jacobi (SRJ) method is an extension of the classical Jacobi iterative metho...
International audienceIn the framework of linear problems, a usual approach to study the convergence...
Abstract: Non-linear renewal theory is extended to include random walks perturbed by both a slowly c...
Extrapolation methods to accelerate convergence of a sequence of iterates are in-vestigated. A trans...
International audienceWe study convergence rates of R-d-valued algorithms, especially in the case of...
The connection between the conditioning of a problem instance -- the sensitivity of a problem instan...
We propose a new approach to analyze the convergence of optimized Schwarz waveform relaxation (OSWR)...
AbstractWe obtain rates of convergence of stochastic relaxation (heat bath algorithm) for continuous...
The problem (LFP) of finding a feasible solution to a given linear semi-infinite system arises in d...
Convergent sequences of real numbers play a fundamental role in many different problems in system th...